mrkeyoor.com_
Fri 18 Sept 08:50 UTC
Self-Hostedevaluationupdated 26 Aug 2026

TencentDB-Agent-Memory review

TencentDB Agent Memory is a self-hosted memory hub that turns agent conversations, documents, code, and repeatable work into shared assets. It gives supported coding agents a proxy through which they can retrieve team-approved memories, skills, wiki pages, and code relationships across sessions.

+526stars / 7d
Verdict

Our MemoryCore install used 966 MB, then its build and tests both exited 1, while npm audit found 24 known vulnerabilities. The team asset and access model is worth a sandbox trial for organizations using several coding agents, but v2.0.1 is not ready for blind production adoption from source. Wait if you cannot own 3 services, 2 LLM configurations, proxy routing, data review, and upgrade testing.

We ran it

Lab card: what happened when we ran TencentDB-Agent-MemoryScreenshot of TencentDB-Agent-Memory (github.com/TencentCloud/TencentDB-Agent-Memory)
Install✓ · 103s541 packages · 966 MB
Build✗ · 9s
Tests✗ · 5sran, no count parsed
Known vulns240 critical · 2 high · 22 moderate · 0 low (npm audit)
Repo930 files~197,413 lines of source · 42.9 MB · 1 CI workflows · Dockerfile

Answers from our run

Does TencentDB-Agent-Memory build from source?

Dependencies installed in 103 seconds (541 packages), and the build failed. We cloned commit 97f9465 into a clean Debian container with 3 CPUs and no project-specific setup.

Do TencentDB-Agent-Memory's tests pass?

The test command failed in our container, and its output did not report a pass or fail count.

Does TencentDB-Agent-Memory have known vulnerabilities in its dependencies?

npm audit flagged 24 known advisories in the dependency tree at the time of our run.

Who should not use TencentDB-Agent-Memory?

Teams seeking a one-process memory library: the documented deployment starts Memory Core, Memory Hub, and a proxy, with two groups of LLM settings.

What are the alternatives to TencentDB-Agent-Memory?

Mem0, Graphiti, Letta. Our MemoryCore install used 966 MB, then its build and tests both exited 1, while npm audit found 24 known vulnerabilities.

Setup2/5Install passed, but build and test commands both failed
Docs4/5English install, client, API, and architecture material is extensive
Community4/524,583 stars and active August issues, releases, and responses
Maturity2/5Fast-moving v2 with broken source checks and open integration defects

Who it’s for

Teams using several coding agents that keep paying to explain the same project context.
Operators who need private, team, and restricted visibility for agent knowledge.
Claude Code, Codex, OpenCode, Hermes, OpenClaw, or CodeBuddy users willing to route model traffic through a proxy.
Organizations prepared to review automatically extracted memory before wider sharing.

Who it’s NOT for

Teams seeking a one-process memory library: the documented deployment starts Memory Core, Memory Hub, and a proxy, with two groups of LLM settings.
Buyers who need a clean source verification today: our build failed on a missing scripts/seed-v2/tsconfig.json, and Vitest found no test files.
Security policies that forbid install scripts modifying another product: open issue 1095 says the npm postinstall patches an installed OpenClaw by default.
Private-repository indexing that must work without adaptation: the README says private repository and SSH support is still being refined.
Users expecting automatic memory selection to be finished: the README says fully automatic routing remains under iteration.

Setup reality

Our MemoryCore/ install succeeded in 103 seconds, adding 541 npm packages and using 966 MB. The build failed after 9 seconds because scripts/seed-v2/tsconfig.json did not exist. Tests failed after 5 seconds because Vitest found no matching test files.

The full deployment starts 3 services and asks for 2 sets of LLM endpoint, model, and API-key settings. Agent clients point their model base URL at the proxy, while the Hub handles users, teams, assets, bindings, and access rules.

The checkout had 930 files, about 197,413 source lines, and 42.9 MB. Npm audit reported 24 known vulnerabilities: 2 high and 22 moderate. Docker networking and public base URLs also need care when agents run on the host while services run in containers.

Four asset types give agent memory an owner and an audience

TencentDB Agent Memory stores more than conversation snippets. It turns chats into layered memories, finished work into reusable skills, documents into linked wiki pages, and repositories into code graphs. The Hub tracks ownership, versions, visibility, and agent bindings for these assets. That structure addresses a real team problem: useful context often exists, but the next agent cannot find it or should not see all of it.

Visibility has explicit modes for private, team, restricted, and agent-bound material. The README says private assets remain visible only to their owner, while restricted assets can use user, role, or agent rules. This is a stronger starting point than copying a shared prompt into every client. It still requires humans to review extracted facts and skills before trusting or sharing them.

Three services and two model configurations sit behind the quick start

The installation guide starts Memory Core, Memory Hub, and a proxy through the global-images deployment. Before launch, the operator copies an environment file and fills 2 sets of LLM settings: one for memory work and another for proxied agent traffic. The panel then runs on port 8125, and each supported agent receives a base URL and user key.

This arrangement avoids writing a plugin for every client, but it puts the proxy in the model request path. Outages, wrong public URLs, or identity mismatches can remove memory and may block the agent itself. Open issue 1144 documented host-side Codex failures caused by container-only addresses, a missing Codex session prefix, and incomplete knowledge injection. The report includes a later verification of its proposed fixes, yet the networking lesson remains relevant.

What happened when we ran it

Our sandbox cloned commit 97f9465 and entered MemoryCore/. Npm installed 541 packages in 103 seconds and occupied 966 MB. The repository checkout itself held 930 files, roughly 197,413 source lines, and 42.9 MB. Npm audit reported 24 known vulnerabilities, divided into 2 high and 22 moderate findings.

The build exited 1 after 9 seconds. Several earlier TypeScript stages completed, then build:seed-v2 called the compiler with scripts/seed-v2/tsconfig.json. The final error was TS5058 because that path did not exist. The log identifies a missing project file; it does not show whether the intended fix is restoring the file or removing the stale build step.

Tests exited 1 after 5 seconds. Vitest searched src/**/*.test.ts and __tests__/**/*.test.ts, excluded distribution, dependency, and end-to-end paths, then reported that it found no test files. That means 0 tests ran. It is a configuration or repository-content failure, not a failed assertion, and it leaves our run without automated behavior evidence.

Agent support is broad, while several edges are still moving

The English README lists Claude Code, Codex, DeepSeek Harness, CodeBuddy, WorkBuddy, Hermes, OpenClaw, and a generic adapter path. Release v2.0.1, published August 25, 2026, added more client support and improved onboarding, session binding, skill editing, conversation search, and deployment checks. The release notes themselves are primarily Chinese, while the main README and linked installation material have English versions.

The project says no MCP server or client hook is required because agents use the proxy protocol. That simplicity depends on the proxy correctly identifying sessions and injecting reachable tools. Test each supported client separately, including reset, agent switching, task switching, and a service restart. A successful chat response does not prove that the right memory or wiki was attached.

The npm install side effect needs an explicit policy

Open issue 1095 says installing the published memory package can locate an existing OpenClaw and patch its built distribution files during postinstall. The report notes that current main added logging and a skip variable, while the behavior remained opt-out. An operator installing the package for Hermes could therefore modify a separate OpenClaw installation on the same machine.

That is too surprising for shared production hosts. Inspect the package scripts, use a disposable build environment, and decide whether install scripts are allowed before running npm. If OpenClaw support needs the patch, apply it as a documented deployment step and verify it again after OpenClaw upgrades. Lockfiles will not describe an in-place change to another installed product.

Twenty-four thousand stars arrived before source checks became dependable

GitHub recorded 24,583 stars, 710 combined issues and pull requests, and a last push on August 26, 2026. The v2.0.1 release landed one day earlier. This is unusually fast interest and development for an agent-memory service. It also means configuration and client behavior can change quickly enough that release notes and migration tools are part of normal operation.

The idea is stronger than the current source verification. Shared assets, human-controlled access, and client portability solve problems that simple vector recall does not. The 9-second build failure, empty 5-second test run, 24 audit findings, and open integration reports justify a contained pilot with synthetic data. Keep the proxy away from critical agent work until restarts, permissions, deletion, upgrades, and wrong-memory cases pass your own checks.

Alternatives

ProjectWhat it isPick it when
Mem0 gh↗A memory layer for agents and assistants with local and managed deployment options.pick this instead when application-level memory APIs matter more than a team asset hub and coding-agent proxy.
Graphiti gh↗A temporal knowledge-graph framework for agent memory and changing facts.pick this instead when time-aware entity relationships are central and you want to build your own access and client layer.
LettaAn agent platform built around persistent state and editable memory blocks.pick this instead when the agent runtime itself should own persistent memory rather than sitting behind an existing coding agent.

What people are saying

  1. [github-trending] TencentCloud/TencentDB-Agent-Memory

Sources

  1. TencentDB Agent Memory repository and English README
  2. TencentDB Agent Memory v2.0.1 release
  3. OpenClaw postinstall patch report 1095
  4. Codex and container integration report 1144
  5. Stale vector store handle report 1155

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